code: def export_to_onnx(input_shape, model, file_path):
      input_spec = []
      input_spec.append(
          tf.TensorSpec(input_shape, tf.float32, name="input")
      )
      model_proto, _ = tf2onnx.convert.from_keras(
          model, input_signature=input_spec, output_path=file_path
      )
      print(
          "saved the onnx graph (ready for inference) at: ", file_path
      )
  
file_path: tf-encrypted/examples/application/house-credit-default/main.py
imports: import argparse
  import os
  import time
  import tensorflow
  import tf2onnx
  from tensorflow import keras
  from tensorflow.keras import layers
  from tensorflow.python import errors_impl
  from utils import data_prep
  from utils import read_one_row
label_desc: Use image node_id 1 for calling a global function with example usage: export_to_onnx(input_shape, model, file_path) without return types